Advances in Human Locomotion Using Sensor-Based Approaches
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: 5 February 2025 | Viewed by 628
Special Issue Editors
Interests: neuromuscular control; balance; training; electrical stimulation; electromyography; reflexes; fatigue; aging
Special Issues, Collections and Topics in MDPI journals
Interests: sports and clinical biomechanics; ACL injury; exercise-induced muscle damage; gait analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Gait analysis and the investigation of human locomotion in general are currently undergoing an evolution through the seamless transition from video- to sensor‑based technologies. Traditionally, 3D motion is captured via video recordings of passive or active reflectors placed on body landmarks, which is a laborious process. Inertial Measurement Units (IMUs) technology has emerged as an essential tool for more easily recording kinematics and its derivatives, from joint angles, limb orientation, and angular velocities, to accelerations and forces during walking or running. Complementing IMUs with electromyography (EMG) may provide invaluable insights into neuromuscular control throughout gait phases, providing insights about the neural origin of muscle force production. These technologies may use wireless sensors, which offer greater freedom for movement under more versatile conditions than video-based motion capture, in a laboratory setting as well as in the field. Portable devices that are equipped with diverse sensors may extend gait analysis beyond the laboratory, enabling the continuous monitoring of movement patterns in various conditions and populations. Under these circumstances, artificial intelligence (AI) techniques, such as machine learning and deep learning, are emerging as valuable tools for movement analysis. For instance, these AI techniques may facilitate the extraction of meaningful insights from vast datasets, aiding in the identification of subtle gait deviations and enabling the prediction of future gait-related conditions, such as knee osteoarthritis or Parkinson’s disease. Therefore, these technologies collectively hold promise for clinical applications, facilitating the early detection of gait impairments, monitoring disease progression, and guiding personalized treatment strategies for patients. These methods can also be applied in sports, ergonomics (e.g., shoe technology), and other setups regarding human movement, facilitating our understanding of movement patterns, limb coordination, and modular muscle activation under challenging conditions (e.g., tripping, slipping, obstacle avoidance, etc.) and the adaptability of the neuromuscular system after training or injuries during walking or running. Overall, the landscape of gait analysis as a new technology is emerging and may provide a more comprehensive understanding of human locomotion in clinical settings, sports, and everyday activities.
This Special Issue aims to provide a holistic overview of gait analysis focusing on kinematic, dynamic, and neuromuscular aspects of human locomotion. Therefore, we invite authors to submit review or original research manuscripts that contribute to an interdisciplinary dialogue regarding our understanding in human locomotion using sensor-based approaches. The main goal of this Special Issue is to contribute to the shaping of the future of gait analysis for improved patient outcomes, advances in injury prevention, and optimized athletic performance.
The main topics to be covered in this Special Issue include, but are not limited to, the following:
- Exploring innovative applications and methodologies in IMU-based gait analysis, with a specific focus on kinematics and dynamics.
- Sharing findings on the application of EMG sensors in gait analysis, with emphasis on how novel EMG techniques contribute to a comprehensive understanding of muscle activity during phases of walking or running.
- Highlighting the potential of portable, sensor-based devices for real-world gait analysis and emphasizing their clinical and sports applications for diverse populations and conditions.
- Contributions that explore limb coordination and muscle modalities using sensor technologies and artificial intelligence.
We look forward to receiving your contributions.
Dr. Dimitrios A. Patikas
Dr. Themistoklis Tsatalas
Guest Editors
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- gait
- running
- motion analysis
- biomechanics
- ergonomics
- muscle modules
- artificial intelligence
- wearable sensors
- movement disorders
- musculoskeletal injuries
